Biology subjects

Bardon, G.

Publications and source records attributed to Bardon, G..

9 recordsLinked to original sources

bioRxiv2026

An epigenetic palimpsest: the King penguin's blood methylome reveals conserved hematopoietic ageing

Age-associated DNA methylation is conserved across vertebrates, but whether epigenetic ageing reflects cellular ageing programmes or age-dependent shifts in cell composition remains unresolved. Here, using 126 whole-blood methylomes from known-age King penguins (Aptenodytes patagonicus), we exploit a vertebrate system in which nucleated erythrocytes dominate peripheral blood, minimizing the influence of leukocyte heterogeneity. We identify a core set of 409 ageing-associated genes showing lifelong, clock-like methylation change. These genes are strongly enriched for regulators of hematopoietic stem and progenitor cell (HSPC) function and niche communication. Integration of methylome, transcriptome and chromatin-accessibility data reveals that many of the strongest ageing signals derive from genes inactive in mature erythrocytes, consistent with the persistence of epigenetic states from ancestral hematopoietic progenitors. A comparison with methylation profiles from 1,501 humans identified a conserved cross-species subset of ageing genes, and a human epigenetic age model constructed solely from orthologues of penguin ageing genes predicts chronological age with high accuracy while remaining largely insensitive to blood cell composition. We propose that blood epigenetic ageing signatures contain a long-lived cellular memory of stem-cell ageing, that may represent an evolutionarily ancient layer of the vertebrate ageing process.

systems biology↗

bioRxiv2026

The BEAC, an epigenetic clock for birds

Epigenetic clocks are powerful tools for estimating both chronological and biological age, enabling the integration of age information into population monitoring, demographic modelling, and research on the ecophysiology and evolution of ageing. Most epigenetic clocks so far have been developed for mammals: here, we present the Bird Epigenetic Ageing Clock (BEAC) for estimating chronological age in avian species. BEAC was established based on genome-wide enzymatic methylation sequencing data of known-age king penguins (Aptenodytes patagonicus), and validated in nine other bird species. The BEAC collects age-informative signals into a bisulfite amplicon sequencing panel of 24 primer pairs, providing a highly accurate and cost-effective alternative to sequencing-intensive approaches. It achieved strong predictive performance in independent king penguin training (R{superscript 2}=0.88; MAE=1.7 years, n=78) and testing data (R{superscript 2}=0.79; MAE=2.3 years, n=41), with negligible batch effects, high longitudinal consistency, and resilience to reduced sample size or missing loci. Importantly, cross-species validation across 180 samples showed that BEAC reliably captures age-associated methylation signals in nine additional bird species across seven clades, demonstrating that a single set of loci can be predictive of ageing across multiple different bird species. BEAC offers a flexible, empirically validated tool and a transferable framework for developing epigenetic clocks in avian species, providing a highly valuable resource for eco-evolutionary studies of ageing in wild species.

molecular biology↗

bioRxiv2026

Monte Carlo simulations to propagate the uncertainty of machine-learning classification into ecological models

Deep learning (DL) is increasingly integrated into quantitative ecology, particularly for automating the classification of sensor data in biodiversity monitoring. In addition to substantially reducing data processing effort, DL models often achieve high classification performance. However, despite ongoing improvements, certain species or classification tasks remain challenging, and predictions are rarely error-free. Manual verification is frequently included into data processing pipelines to mitigate misclassifications, but this approach may mask rather than quantify uncertainty. Here, we propose directly incorporating classification uncertainty into ecological inference, rather than filtering it afterwards. Specifically, we treat model predictions as probabilistic outputs rather than fixed class assignments, by using Monte Carlo simulations to propagate uncertainty from the classification process into downstream ecological models. We illustrate this approach using two case studies. The first estimates stochastic population growth rates for a penguin population using detection time series derived from Radio Frequency IDentification (RFID). The second propagates uncertainty in species identification from camera trap images into occupancy estimates. For both, we compare results obtained propagating classification uncertainty with those from conventional single-class attribution at two confidence score thresholds. Our findings show that propagating uncertainty typically leads to higher, more optimistic ecological estimates compared to the single-class confidence approach. Importantly, this method expands the total uncertainty interval by explicitly introducing the confidence score produced by automatic classification as a representation of uncertainty. Quantifying this uncertainty in parameter estimation allows for more informed and reliable ecological interpretations. Monte Carlo simulations offer a flexible and accessible means to integrate classification uncertainty into diverse ecological modelling workflows.

ecology↗

bioRxiv2025

Multiannual environmental forcing shapes breeding phenology and success in a subantarctic seabird

Climate-driven phenological mismatches threaten avian reproduction by disrupting food availability during critical breeding stages. In marine ecosystems, time lags between environmental changes and their effects on food webs are challenging to model, yet they can have a profound impact on top-predator reproduction. We disentangle how oceanic and climatic variability influence the breeding phenology and success of a keystone seabird of the Southern Ocean drawing on 24 years of data from 17,000 marked king penguins. We document an exceptional 19-day advancement in breeding phenology, alongside increased breeding success (44% in 2000, 62% in 2023). A sliding-window analysis reveals that sea temperature and primary production in key foraging zones predict both phenology and breeding success, with lags ranging from several weeks to two years. While king penguins appear to be keeping pace with current changes, their dependence on multi-year environmental conditions underscores the vulnerability of top predators to unpredictable, fast-changing, and more frequent extreme conditions.

ecology↗

bioRxiv2025

Early-life stress as a potential resilience factor in king penguins

Climate change-driven environmental variability can cause species to shift their phenology, leading to an increase in phenological mismatches. Whether the fitness cost of such mismatches can be mitigated by plasticity remains poorly understood, especially in the context of wild populations. In this study, we quantified responses to phenological mismatch using capture-mark-recapture, morphological, and transcriptomic data from king penguins hatching during and after the seasonal peak of food availability (i.e., born early and late in the breeding season, respectively). Late-born chicks showed reduced survival to fledging and fledged smaller and in slightly poorer body condition than chicks born during the seasonal peak in food availability. Yet post-fledging return rates did not differ between late- and early-born chicks, suggesting that early-life stress was effectively mitigated among individuals that survived to fledging, with no detectable carryover effects in the first years post-fledging. Genes involved in oxidative stress response, homeostasis, and nutrient-sensing were differentially expressed between early- and late-born chicks, consistent with stress mitigation and homeostasis maintenance at the expense of growth in late-born chicks. A co-expression gene cluster whose primary expression pattern was associated with hatching phenology also contained central genes involved in stress mitigation. Together, our findings highlight molecular mechanisms that buffer the fitness costs of phenological mismatch, which may allow species to tolerate mismatch to some extent. Despite higher winter mortality of individuals born in mismatch, the plastic response observed in survivors hints towards molecular adaptations that could allow species resilience under increasing climate-driven environmental unpredictability.

genomics↗

bioRxiv2025

Flexible foraging effort shapes Adelie penguin reproductive success across Antarctica and sea ice conditions

Understanding how species deal with diverse environmental conditions is crucial for predicting their future responses to climate change. In Antarctica, changing sea ice dynamics threaten ice-dependent species. Whilebehavioural adjustmentscould help mitigate these threats, their effectiveness under future environmental conditions and potential thresholds remain unclear. Long-term studies and circumpolar approaches could address this challenge. Our 15-year study (2010-2024) of over 23,000 foraging trips from Adelie penguins (Pygoscelis adeliae) in East Antarctica, identified a non-linear relationship between sea ice concentration (SIC) and foraging effort when landfast ice was absent, a situation anticipated to define the species future habitat during chick-rearing. Minimal effort occurred at 10-20% SIC, but more than doubled with the presence of landfast ice or heavy pack-ice, with females showing greater sensitivity to these ice changes. Acircumpolar analysis of similar data demonstrated that foraging effort during chick-guarding predicted reproductive success across ten Adelie penguin populations. Reproductive success remained high until foraging trips exceeded approximately 29 hours, after which performance declined sharply. This indicates that while behavioural flexibility can buffer against moderate environmental changes, it has clear limits. Our findings establish foraging trip duration as a valuable early warning indicator for population responses to environmental change.

ecology↗

bioRxiv2024

Sedentary life accelerates epigenetic ageing in King penguins

Introductory paragraphAdvances in medicine and food security have contributed to an increase in human lifespan1. Yet, the associated rise in sedentary behaviour and in obesity2,3 already threatens these gains4. Indeed, a growing body of evidence supports the central role of nutrient sensing and energy management pathways in regulating ageing rate and healthspan5,6, but the diversity of human lifestyles challenges our ability to identify the genetic and epigenetic drivers of this age acceleration. Here, we examine how the transition of wild King penguins to zoo husbandry can closely mimic the shift to a Western lifestyle in humans, and shed light on evolutionarily conserved epigenetic changes in responses to sedentary conditions. We show that, just like modern humans, zoo-housed King penguins experience an extended lifespan, but this comes at the cost of accelerated epigenetic ageing throughout life. This accelerated ageing is associated with differential methylation in key growth and maintenance pathways including the mTOR and PI3K/Akt networks, as well as in specific pathways of lipid-rich diet adaptation and heart-function. Our results demonstrate the deeply conserved link between sedentary behaviour and food availability on the one hand, and age acceleration on the other. Such evolutionary evidence may in turn help us to improve risk detection and, ultimately, therapeutics for lifestyle-induced age acceleration in humans7.

genomics↗

bioRxiv2024

Declining juvenile survival of Adelie penguins in Antarctica

As summer sea ice around Antarctica reaches modern lows, quantifying the demographic response of polar species to such environmental changes becomes critical. To achieve this, synthesizing results across species ranges and elucidating the environmental factors driving population dynamics are key. Adelie penguins are considered reliable indicators of changes in Antarctica but the processes through which sea ice and other environmental factors shape their population dynamics are still unclear, especially for critical age groups such as juveniles. Using a 17-year dataset of Adelie penguins electronically tagged in Adelie Land (Antarctica), we found that juvenile survival probability was most impacted by sea ice concentration near their natal colony right after fledging, with lower ice concentrations detrimental to survival. Importantly, we found that juvenile survival declined by 32% from 2007 to 2020, mirroring trends at other distant colonies. The emergence of similar patterns at opposite ends of the continent may be an early signal for shifts in population trends expected from climate change.

ecology↗

bioRxiv2023

RFIDeep: Unfolding the Potential of Deep Learning forRadio-Frequency Identification

O_LIAutomatic monitoring of wildlife is becoming a critical tool in the field of ecology. In particular, Radio-Frequency IDentification (RFID) is now a widespread technology to assess the phenology, breeding, and survival of many species. While RFID produces massive datasets, no established fast and accurate methods are yet available for this type of data processing. Deep learning approaches have been used to overcome similar problems in other scientific fields and hence might hold the potential to overcome these analytical challenges and unlock the full potential of RFID studies. C_LIO_LIWe present a deep learning workflow, coined "RFIDeep", to derive ecological features, such as breeding status and outcome, from RFID mark-recapture data. To demonstrate the performance of RFIDeep with complex datasets, we used a long-term automatic monitoring of a long-lived seabird that breeds in densely packed colonies, hence with many daily entries and exits. C_LIO_LITo determine individual breeding status and phenology and for each breeding season, we first developed a one-dimensional convolution neural network (1D-CNN) architecture. Second, to account for variance in breeding phenology and technical limitations of field data acquisition, we built a new data augmentation step mimicking a shift in breeding dates and missing RFID detections, a common issue with RFIDs. Third, to identify the segments of the breeding activity used during classification, we also included a visualisation tool, which allows users to understand what is usually considered a "black box" step of deep learning. With these three steps, we achieved a high accuracy for all breeding parameters: breeding status accuracy = 96.3%; phenological accuracy = 86.9%; breeding success accuracy = 97.3%. C_LIO_LIRFIDeep has unfolded the potential of artificial intelligence for tracking changes in animal populations, multiplying the benefit of automated mark-recapture monitoring of undisturbed wildlife populations. RFIDeep is an open source code to facilitate the use, adaptation, or enhancement of RFID data in a wide variety of species. In addition to a tremendous time saving for analyzing these large datasets, our study shows the capacities of CNN models to autonomously detect ecologically meaningful patterns in data through visualisation techniques, which are seldom used in ecology. C_LI

ecology↗